Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Radiation Oncology cung cấp cho các bạn kiến thức về ngành y đề tài: " Development of a neuro-fuzzy technique for automated parameter optimization of inverse treatment planning. | Radiation Oncology BioMed Central Research Open Access Development of a neuro-fuzzy technique for automated parameter optimization of inverse treatment planning Florian Stieler 1 Hui Yan2 Frank Lohr1 Frederik Wenz1 and Fang-Fang Yin2 Address Department of Radiation Oncology University Medical Center Mannheim University of Heidelberg 68167 Mannheim Germany and 2Department of Radiation Oncology Duke University Medical Center Durham NC 27710 USA Email Florian Stieler - Hui Yan - Frank Lohr - Frederik Wenz - Fang-Fang Yin - Corresponding author Published 25 September 2009 Received 18 March 2009 Accepted 25 September 2009 RadiationOncology 2009 4 39 doi l748-7l7X-4-39 This article is available from http content 4 l 39 2009 Stieler et al licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Background Parameter optimization in the process of inverse treatment planning for intensity modulated radiation therapy IMRT is mainly conducted by human planners in order to create a plan with the desired dose distribution. To automate this tedious process an artificial intelligence AI guided system was developed and examined. Methods The AI system can automatically accomplish the optimization process based on prior knowledge operated by several fuzzy inference systems FIS . Prior knowledge which was collected from human planners during their routine trial-and-error process of inverse planning has first to be translated to a set of if-then rules for driving the FISs. To minimize subjective error which could be costly during this knowledge acquisition process it is necessary to find a quantitative method to .
